AI-Assisted Game Debugging with Cicero

Tiago MacHado; Daniel Gopstein; Andy Nealen; Oded Nov; Julian Togelius

doi:10.1109/CEC.2018.8477829

AI-Assisted Game Debugging with Cicero

Tiago MacHado, Daniel Gopstein, Andy Nealen, Oded Nov, Julian Togelius

Technology Management and Innovation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present Cicero, a mixed-initiative application for prototyping two-dimensional sprite-based games across different genres such as shooters, puzzles, and action games. Cicero provides a host of features which can offer assistance in different stages of the game development process. Noteworthy features include AI agents for gameplay simulation, a game mechanics recommender system, a playtrace aggregator, heatmap-based game analysis, a sequential replay mechanism, and a query system that allows searching for particular interaction patterns. In order to evaluate the efficacy and usefulness of the different features of Cicero, we conducted a user study in which we compared how users perform in game debugging tasks with different kinds of assistance.

Original language	English (US)
Title of host publication	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509060177
DOIs	https://doi.org/10.1109/CEC.2018.8477829
State	Published - Sep 28 2018
Event	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brazil Duration: Jul 8 2018 → Jul 13 2018

Publication series

Name	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

Other

Other	2018 IEEE Congress on Evolutionary Computation, CEC 2018
Country/Territory	Brazil
City	Rio de Janeiro
Period	7/8/18 → 7/13/18

Keywords

AI for Games
AI-Assisted Game Design Tools
Game Debugging
Game Design
Game Prototyping

ASJC Scopus subject areas

Artificial Intelligence
Control and Optimization

Access to Document

10.1109/CEC.2018.8477829

Cite this

MacHado, T., Gopstein, D., Nealen, A., Nov, O., & Togelius, J. (2018). AI-Assisted Game Debugging with Cicero. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings Article 8477829 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2018.8477829

AI-Assisted Game Debugging with Cicero. / MacHado, Tiago; Gopstein, Daniel; Nealen, Andy et al.
2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8477829 (2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

MacHado, T, Gopstein, D, Nealen, A, Nov, O & Togelius, J 2018, AI-Assisted Game Debugging with Cicero. in 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings., 8477829, 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, 7/8/18. https://doi.org/10.1109/CEC.2018.8477829

@inproceedings{0d533929bff340ce9381e0a1accf8e62,

title = "AI-Assisted Game Debugging with Cicero",

abstract = "We present Cicero, a mixed-initiative application for prototyping two-dimensional sprite-based games across different genres such as shooters, puzzles, and action games. Cicero provides a host of features which can offer assistance in different stages of the game development process. Noteworthy features include AI agents for gameplay simulation, a game mechanics recommender system, a playtrace aggregator, heatmap-based game analysis, a sequential replay mechanism, and a query system that allows searching for particular interaction patterns. In order to evaluate the efficacy and usefulness of the different features of Cicero, we conducted a user study in which we compared how users perform in game debugging tasks with different kinds of assistance.",

keywords = "AI for Games, AI-Assisted Game Design Tools, Game Debugging, Game Design, Game Prototyping",

author = "Tiago MacHado and Daniel Gopstein and Andy Nealen and Oded Nov and Julian Togelius",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Congress on Evolutionary Computation, CEC 2018 ; Conference date: 08-07-2018 Through 13-07-2018",

year = "2018",

month = sep,

day = "28",

doi = "10.1109/CEC.2018.8477829",

language = "English (US)",

series = "2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings",

}

TY - GEN

T1 - AI-Assisted Game Debugging with Cicero

AU - MacHado, Tiago

AU - Gopstein, Daniel

AU - Nealen, Andy

AU - Nov, Oded

AU - Togelius, Julian

PY - 2018/9/28

Y1 - 2018/9/28

N2 - We present Cicero, a mixed-initiative application for prototyping two-dimensional sprite-based games across different genres such as shooters, puzzles, and action games. Cicero provides a host of features which can offer assistance in different stages of the game development process. Noteworthy features include AI agents for gameplay simulation, a game mechanics recommender system, a playtrace aggregator, heatmap-based game analysis, a sequential replay mechanism, and a query system that allows searching for particular interaction patterns. In order to evaluate the efficacy and usefulness of the different features of Cicero, we conducted a user study in which we compared how users perform in game debugging tasks with different kinds of assistance.

AB - We present Cicero, a mixed-initiative application for prototyping two-dimensional sprite-based games across different genres such as shooters, puzzles, and action games. Cicero provides a host of features which can offer assistance in different stages of the game development process. Noteworthy features include AI agents for gameplay simulation, a game mechanics recommender system, a playtrace aggregator, heatmap-based game analysis, a sequential replay mechanism, and a query system that allows searching for particular interaction patterns. In order to evaluate the efficacy and usefulness of the different features of Cicero, we conducted a user study in which we compared how users perform in game debugging tasks with different kinds of assistance.

KW - AI for Games

KW - AI-Assisted Game Design Tools

KW - Game Debugging

KW - Game Design

KW - Game Prototyping

UR - http://www.scopus.com/inward/record.url?scp=85056282058&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056282058&partnerID=8YFLogxK

U2 - 10.1109/CEC.2018.8477829

DO - 10.1109/CEC.2018.8477829

M3 - Conference contribution

AN - SCOPUS:85056282058

T3 - 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

BT - 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Congress on Evolutionary Computation, CEC 2018

Y2 - 8 July 2018 through 13 July 2018

ER -

AI-Assisted Game Debugging with Cicero

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this